This study identifies key challenges in hydrogen storage and proposes computational strategies to design more effective storage materials for next-generation energy systems.

Molecular dynamics simulations of ionic interactions in porous carbon electrodes reveal ion-dependent changes to the electrode structure and highlight the importance of considering electrode flexibility when modeling these systems.

Using theoretical first-principles methods, stable and metastable phases of silver-based chalcohalide anti-perovskites are predicted, offering insight into their stability for potential energy and optoelectronic applications.

A data analytics platform distills mineral commodity information from a large database to create accessible insights for researchers, policymakers, and industry shareholders. Such insight into the global supply chain can inform decisions around sustainable materials and renewable energy technologies.

A neural network potential model is developed for ZnCl${}_2$ electrolytes that provides atomic scale insights into the solvation structure and ionic conductivity. The results agree well with experiment and shed light on the performance of aqueous zinc-ion batteries across a wide concentration range of ZnCl${}_2$ electrolytes.

Advanced luminescence microscopy reveals that metastable nonradiative centers in metal-halide perovskites have a hybrid two-level structure, likely formed by associated simple defects.

This study devises a route to improve the optoelectronic properties of tin-halide perovskites. Using hybrid density functional theory calculations, a donor doping strategy is developed that aims to significantly decrease observed free hole concentrations in these materials.

Using the JET tokamak, the study demonstrates feedback control of tritium concentration in a deuterium-tritium plasma, independently of total gas injection.

A proposed framework quantifies and compares the energy consumption of quantum and classical computation, suggesting that quantum computers can solve a type of problem using much less energy than any classical counterpart.

A theoretical framework highlights the importance of accounting for differences in ion diffusivities when modeling ionic transport. This approach enhances the accuracy of impedance modeling in nanoporous electrodes and may be extended to a broader range of electrochemical systems.

Charge transport in photoelectrodes for photoelectrochemical cells is influenced by microstructural variations; here, the authors use Kelvin Probe Force Microscopy to correlate local morphology with optoelectronic properties toward optimizing materials toward material optimization.

This study presents a protocol for mitigating environment-induced energy loss in quantum batteries.

This study demonstrates a 1000-fold enhancement in energy storage lifetime for Dicke-model-based quantum batteries by leveraging molecular triplet states to suppress radiative losses.